content: package org.df4j.tricky.aggregate;
  /*
   * Licensed to the Apache Software Foundation (ASF) under one or more
   * contributor license agreements.  See the NOTICE file distributed with
   * this work for additional information regarding copyright ownership.
   * The ASF licenses this file to You under the Apache License, Version 2.0
   * (the "License"); you may not use this file except in compliance with
   * the License.  You may obtain a copy of the License at
   *
   *    http://www.apache.org/licenses/LICENSE-2.0
   *
   * Unless required by applicable law or agreed to in writing, software
   * distributed under the License is distributed on an "AS IS" BASIS,
   * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
   * See the License for the specific language governing permissions and
   * limitations under the License.
   */
  
  import org.df4j.core.util.Pair;
  
  import java.util.concurrent.ConcurrentHashMap;
  import java.util.function.BiFunction;
  
  /**
   * a class to make reduce operation similar to Spark's RDD::reduceByKey
   * @param <K>
   */
  public final class ReduceByKey<K, V> extends ConcurrentHashMap<K, ReducingActor> {
    final BiFunction<V,V,V> reducer;
  
    public ReduceByKey(BiFunction<V,V,V> reducer) {
      this.reducer = reducer;
    }
  
    public void reduceByKey(K key, V value) {
      Pair<K, V> msg = new Pair<>(key, value);
      ReducingActor actor = computeIfAbsent(key,
              (key1) -> new ReducingActor(key1, reducer));
      actor.onNext(msg);
    }
  
    public void onComplete() {
      for (ReducingActor actor: values()) {
        actor.onComplete();
      }
    }
  
  }
  